Introduction to GRASS GIS

Which GRASS?

• GRASS GIS (Geographic Resources Analysis Support System), a FOSS suite used for geospatial data management and analysis, image processing, graphics and maps, spatial modeling, and visualization.

• Originally developed by the U.S. Army Construction Engineering Research Laboratories for land management and environmental planning (1982-1995).

• More history: https://grass.osgeo.org/about/history/

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A bit of (geek) GRASS GIS history…

In case you didn’t notice, the video is narrated by William Shatner 🚀

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GRASS GIS general stuff

• Free and open source, you can use, modify, improve, share
• Strong user community, commercial support
• Large amount of tools: 500+ core modules, 300+ addons
• GUI and CLI interfaces
• Python API and libraries - new grass.jupyter library can be tried online
• Connection with R, QGIS, WPS, etc.
• Different data types supported: raster (including satellite imagery), 3D raster or voxel, vector and space-time datasets

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More than 500 core modules

Prefix	Function class	Type of command	Example
g.*	general	general data management	g.rename: renames map
d.*	display	graphical output	d.rast: display raster map
r.*	raster	raster processing	r.mapcalc: map algebra
v.*	vector	vector processing	v.clean: topological cleaning
i.*	imagery	imagery processing	i.pca: Principal Component Analysis
r3.*	voxel	3D raster processing	r3.stats: voxel statistics
db.*	database	database management	db.select: select value(s) from table
ps.*	postscript	PostScript map creation	ps.map: PostScript map creation
t.*	temporal	space-time datasets	t.rast.aggregate: raster time series aggregation

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More than 300 add-ons

Plugins or Add-ons can be installed from a centralized OSGeo repository or from github (or similar repositories) using g.extension command.

# install extension from GRASS GIS Add-on repository
g.extension extension=r.hants
 
# install extension from github repository
g.extension extension=r3.slice \
  url=https://github.com/petrasovaa/r3.slice

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Graphical User Interface (GUI)

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Command line

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GRASS + R through rgrass package

We can use R within a GRASS GIS session or use GRASS GIS within an R session

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Temporal support in GRASS GIS

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The TGRASS framework

GRASS GIS was the first FOSS GIS that incorporated capabilities to manage, analyze, process and visualize spatio-temporal data, as well as the temporal relationships among time series.

• TGRASS is fully based on metadata and does not duplicate any dataset
• Snapshot approach, i.e., adds time stamps to maps
• A collection of time stamped maps (snapshots) of the same variable are called space-time datasets or STDS
• Maps in a STDS can have different spatial and temporal extents

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Space-time datasets

• Space time raster datasets (STRDS)
• Space time 3D raster datasets (STR3DS)
• Space time vector datasets (STVDS)

Upcoming GRASS 8 will support image collections by adding a band reference

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Temporal modules

• t.*: General modules to handle STDS of all types
• t.rast.*: Modules that deal with STRDS
• t.rast3d.*: Modules that deal with STR3DS
• t.vect.*: Modules that deal with STVDS

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Other TGRASS notions

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• Time can be defined as intervals (start and end time) or instances (only start time)
• Time can be absolute (e.g., 2017-04-06 22:39:49) or relative (e.g., 4 years, 90 days)
• Granularity is the greatest common divisor of the temporal extents (and possible gaps) of all maps in the space-time cube

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• Topology refers to temporal relations between time intervals in a STDS.

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TGRASS framework and workflow

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Walk through space-time analysis for disease ecology with GRASS GIS and :r-project:

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Demo session overview

Habitat suitability mapping for the Asian tiger mosquito in Northern Italy based on variables derived from daily LST data

• GRASS
  • Import species records
  • Create random background points
  • Create different environmental layers from daily LST data
• R
  • Read data from GRASS into R
  • Model species distribution
  • Model evaluation
  • Visualization of results

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Jarnevich et al. 2015. doi:10.1016/j.ecoinf.2015.06.007

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Data for the session

• Records of Aedes albopictus (Asian tiger mosquito) in Northern Italy downloaded from GBIF
• Daily MODIS LST reconstructed by mundialis based on Metz et al. 2017
  • 1 km spatial resolution
  • Converted to Celsius degrees

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:download: Get sample location, mosquito records and code :download:

• Create a folder named grassdata_ogh
• Download and unzip eu_laea location with LST mapset and unzip within your grassdata_ogh folder
• Download the asian tiger mosquito occurrences as .gpkg file
• Download the GRASS script
• Download the R script

The grassdata_ogh folder’s tree should look like this:

  grassdata_ogh/
  └── eu_laea
      ├── italy_LST_daily
      └── PERMANENT

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